System and method for low-loss removal of stationary and non-stationary short-time interferences

ABSTRACT

According to a preferred aspect of the instant invention, there is provided a system and method that allows the user to remove stationary and not stationary short time interference signals in speech or other recordings in the audio part of a video recording. The system is automatically analyzing the input signal and in a plurality of individual steps detects the interference signal and removes it accordingly.

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 61/987,236 filed on May 1, 2014, and incorporatessaid provisional application by reference into this document as if fullyset out at this point.

FIELD OF THE INVENTION

The present invention relates to the general subject matter of creatingand analyzing video works and, more specifically, to systems and methodsfor analyzing the audio part of video recordings to attenuate ambientnoise.

Removal or attenuation of ambient noise in video recordings is a subjectmatter in which a number of different approaches exist, all trying to bethe most effective solution without harming the integrity of the inputsignal. Many known methods to attenuate or remove ambient noise in videorecordings at the current state of the art utilize the principle of“spectral subtraction”. In this approach a filter function is determinedby estimating the average magnitude of the interfering signal andsubtracting it from the magnitude of the target signal. Thecharacteristics of the interfering signal can be automaticallydetermined by a targeted search for unwanted components which might befound, for example, in breaks between the speech (or other target)content with the audio material. Another way to determine an estimate ofthe interfering signal is to let the user define a noise sample—a sampleof audio material that contains only or predominantly the interferingsignal. This approach is well-known and is often utilized in softwarebased solutions.

The approaches known in the state of the art typically operate bydetermining the average of short time magnitudes of the interferingsignal. This averaging is useful for interfering signals with astochastic character such as ambient noise or for stationary interferingsignals such as a buzzing-type signal. Interfering signals from motors,especially zoom- and autofocus motors in digital cameras usually exhibita non-stationary behavior: The sound behavior of the interference can bevariable and its frequency response often changes fluently/continuously.For a zoom motor the pitch will generally depend on the intended focallength, respectively on the focal length of the objective that has beenpassed through during the set up process. In this case the averaging ofthe short time magnitude of the interfering signal would lead to a broadband filtering which would unnecessarily remove substantial parts of theinput signal.

Methods according to the state of the art usually implement thefiltering process continuously for the whole length of the impairedinput signal. In the case of an interfering signal that only occursintermittently the input signal will also be subjected to a filteringprocess in the undisturbed passages that are often longer, ultimatelyleading to a deterioration of the audio quality of the input signal inthese undisturbed passages.

Heretofore, as is well known in the media editing industry, there hasbeen a need for an invention to address and solve the above-describedproblems. Accordingly it should now be recognized, as was recognized bythe present inventors, that there exists, and has existed for some time,a very real need for a system and method that would address and solvethe above-described problems.

Before proceeding to a description of the present invention, however, itshould be noted and remembered that the description of the inventionwhich follows, together with the accompanying drawings, should not beconstrued as limiting the invention to the examples (or preferredembodiments) shown and described. This is so because those skilled inthe art to which the invention pertains will be able to devise otherforms of the invention within the ambit of the appended claims.

SUMMARY OF THE INVENTION

There is provided herein a system and method for removal or attenuationof interfering noise in audio material, and especially where the targetsignal is speech contained in the audio portion of video material. Anembodiment removes or attenuates temporarily occurring (e.g., transient)stationary and non-stationary interfering noise, e.g., interference fromzoom and autofocus motors in digital video cameras or digital photocameras with video recording functionality. An embodiment may be appliedonly to the particular passages containing interfering noise.

One embodiment modifies the process of “spectral subtraction” byincorporating a dynamic approach, with the goal being to limit thefiltering electively to only the disturbed or otherwise noisecontaminated portions of the signal.

An embodiment taught herein introduces a modification to the process ofcalculating a filter according to the method of “spectral subtraction”which is described, among others, in Chapter 11 of Vaseghi's “AdvancedSignal Processing and Noise Reduction”, 2000, John Wiley & Sons, thedisclosure of which is incorporated herein by reference as if fully setout at this point. In addition to calculation of the transfer functionby determining the difference between spectral magnitudes, the frequencydomain expression of the transfer function can be down-weighted bysetting it to a value of 0 if the maxima of short time magnitudes of thedisturbed input signal and of the interfering signal match spectrally.With this modification the accuracy of the filtering process will beimproved.

Additionally, an embodiment makes it possible to parameterize thealgorithm in such a way that the transfer function is primarilydetermined by the spectral matching maxima of the short time magnitudesof the input signal and the interfering signal. In this case therelevant tonal parts of the interference will be removed or attenuatedand the rest of the input signal will be only minimally affected.

One object of an embodiment is to modify the standard process of“spectral subtraction” by utilizing the short time magnitude of theinterfering signal that has the highest conformity with the determinedshort time magnitude of the input signal containing the interference.This correspondence is then utilized for the calculation of the transferfunction of the filter, thereby attenuating the interfering signal. Withthis approach it will be possible for the resulting transfer function tostay comparatively narrow-banded, which will impair the input signalmuch less.

In an embodiment, the instant invention will be explained with referenceto four stages that together make up the algorithm for low-loss removalof stationary and non-stationary short time interference. This approachis robust and tolerant of the volume differences between the impairedinput signal and the recorded noise sample of the interference signal.

An embodiment begins with an analysis of the input signal, Component A.This phase is intended to detect the best possible match between anexample of an interfering signal, preferably a sample in which thetarget signal is absent so that noise/interfering signal alone ispresent, with the portions of the input signal that is contaminated bythe same sort of noise and, thus, that contains signal plusinterference. The second Component B is performs an analysis of theinput signal to detect adjacent sections containing evidence ofinterference. Continuing with the present embodiment, the thirdComponent C will remove the interfering signal via adaptive filtering.In the last Component D the transfer function of the adaptive filterwill be determined.

According to an embodiment, with respect to Components C and D,calculation of the removal of the interference signal and calculation ofthe associated transfer function, could be implemented in real time,although that is not a requirement.

According to one embodiment, in Component A the input file or recordingcontaining a noise sample of the interfering signal and the file orrecording containing the impaired input signal will be analyzed and theresults stored in memory. The results of the Component A analysis willbe passed to Component B, whose results will also be stored in memory.The resulting data from Components A and B will then be utilized in thecalculation of the transfer function of the adaptive noise attenuatingfilter generated in Component C handles removal of the interferingnoise, preferably in real time. The data from Component A will be usedto determine which section of the noise sample should be used for thecalculation of the transfer function of the interference noise removingfilter. The data from Component B will be utilized to determine whetheror not dampening of the interference noise is carried out section bysection in full or lesser strength. The level of dampening will be fullyadjustable by the user.

Other embodiments and variations are certainly possible within the scopeof the instant invention and can readily be formulated by those ofordinary skill in the art based on the disclosure herein.

The foregoing has outlined in broad terms the more important features ofthe invention disclosed herein so that the detailed description thatfollows may be more clearly understood, and so that the contribution ofthe instant inventors to the art may be better appreciated. The instantinvention is not limited in its application to the details of theconstruction and to the arrangements of the components set forth in thefollowing description or illustrated in the drawings. Rather theinvention is capable of other embodiments and of being practiced andcarried out in various other ways not specifically enumerated herein.Additionally, the disclosure that follows is intended to apply to allalternatives, modifications and equivalents as may be included withinthe spirit and the scope of the invention as defined by the appendedclaims. Further, it should be understood that the phraseology andterminology employed herein are for the purpose of description andshould not be regarded as limiting, unless the specificationspecifically so limits the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Other objects and advantages of the invention will become apparent uponreading the following detailed description and upon reference to thedrawings in which:

FIG. 1 depicts an operating logic suitable for use with an embodimentwhich contains some details of Components A and B.

FIG. 2 illustrates the steps of associated with adaptive filtering inthe frequency domain for removal of the interfering signal according toone embodiment.

FIG. 3 illustrates the analysis of for the detection of adjacentsections containing interference in a first step.

FIG. 4 illustrates the analysis of for the detection of adjacentsections containing interference in a second step.

FIG. 5 depicts the calculation of the transfer function of the adaptivefilter for removal of the interference signal.

FIG. 6 contains a general example of one possible environment of theinvention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring now to the drawings, wherein like reference numerals indicatethe same parts throughout the several views, there is provided apreferred system and method for low-loss removal of stationary andnon-stationary short-time interferences in audio material and, in someembodiments, in the audio track of video recordings.

As is generally indicated in FIG. 6, at least a portion of the instantinvention could be implemented in form of software running on a user'scomputer 600, where the term “computer” is intended to encompass anyprogrammable device capable of performing signal processing of the sortdescribed herein (including, without limitation, cell phones 650, tabletcomputers 640, etc.). Such a computer will have some amount of programmemory and data storage capability 620 (whether internal, external, oraccessible via a network) as is conventionally utilized by such units.Additionally it is possible that an external camera 610 of some sortwould be utilized with—and will preferably be connectible directly orindirectly (e.g., via removable storage) to—the computer 600 so thatvideo and audio and/or graphic information can be transferred to andfrom the computer. Additionally, some aspects of an embodiment might beperformed within the camera 610. Preferably the camera 610 will be adigital video camera with audio recording capabilities, although that isnot a requirement and in some instances the input might be a recordingobtained via one or more microphones 630 which could be connecteddirectly to the computer or connectable indirectly via removable storageor wireless communication. Further given the modern trend towardincorporation of cameras and microphones into other electroniccomponents (e.g. in handheld computers, cell phones, laptops, etc.)those of ordinary skill in the art will recognize that the camera and/ormicrophone might be integrated into an electronic device rather thanbeing a stand alone component. Although the camera will preferably bedigital in nature, any sort of camera might be used, provided that theproper interface between it and the computer is utilized.

An embodiment preferably begins with the reading of two digital signals105 and 125 into a personal or other computer, to include portablecomputers such as tablet computers, cell phones, etc. The input to box105 is the input or target signal, e.g., the audio part of a videorecording, and the input signal 125 is a noise-only recording or, morespecifically, a digital representation of the noise that contaminatesthe target recording 105. In some cases, the selection of the noise-onlyrecording will be performed at the hands of the user, who might beinstructed to record a sample of the noise, select a passage within thetarget signal that is essentially all noise, etc.

Broadly speaking, the first few steps of the current embodiment analyzethe input to find the best possible matches of a noise sample of theinterference signal 125 with the sections of the impaired (i.e., noiseplus signal) input signal 105. The best matches between the singlesections of the recorded interference signal—the noise sample and thesingle sections of the impaired input signal will be determined in thisembodiment by matching the frequencies of spectral maxima—the peaks. Thenumber of spectral maxima (peaks) with matching frequency can beutilized to determine the quality of the match.

Turning now to the embodiment of FIG. 1, according to a first preferredstep both data files 105 and 125 will be partitioned into overlappingwindows or, equivalently, blocks 110 and 130 which are weighted by awindowing function (e.g., a Gaussian taper, a Hanning taper, a Hammingtaper, etc.). In some embodiments, the amount of overlap betweenadjacent windows might be 75%, but other choices are certainly possible.By utilizing a Fast Fourier Transform (“FFT”) or a similar calculationof frequency content, (e.g., a full Fourier Transform, a Walshtransform, a wavelet transform, etc.) the absolute value the spectralshort time magnitudes of each of the windows will be calculated 115 and135. In some embodiments, a window length of 4096 samples might be used.The sample rate of the input can be freely chosen but often it will bebetween about 16 and 192 kHz. One sample rate that is often useful is44.1 or 48 kHz.

Next, in this embodiment the short time magnitudes will be analyzed toidentify their spectral maxima (peaks) 120 and 140, each of whichcorresponds to a dominant frequency that is present in the signal. Forpurposes of the instant disclosure, the phrase “dominant frequency” willbe used to indicate those frequencies in either the target signal or thenoise signal that correspond to significant peaks in the frequencyspectrum and, more particularly, to those frequencies that correspond tothe largest peaks in the spectrum. In this step the spectral maxima ofthe short time magnitudes of the impaired input signal will be comparedwith the spectral maxima of the short time magnitudes of the noisesample to determine where there is a match of the frequencies in bothsignals 145.

Within each block, typically between 50 and 250 peaks in the frequencyspectrum will be identified as dominant. Preferably, the mostsignificant peaks will be used in the steps that follow. In case ofpassages that are relatively noise-free, the number of peaks identifiedmight be between 10 and 50. The individual short time magnitudes and thepositions of the spectral maxima, the peaks of the noise sample will beidentified and stored at least temporarily, because the locations of thepeaks is used in the calculation of the transfer function of theadaptive interference signal removing filter as discussed below. Methodsof identifying peaks within a spectrum or other digital series are wellknown to those of ordinary skill in the art.

In a further step, the signals will be analyzed to detect portions ofthe target signal that are contiguous to sections that have already beenflagged as containing interfering noise 155. One aim of this step is toutilize the results from component A to determine the sections of thenoise contaminated input signal in which the impairing noise is presentin windows other than those already identified. Of course, one reasonfor performing this step is that if a block is determined to becontaminated by noise it will often be the case that blocks adjacent toit (either earlier or later in time) will also be contaminated by noise.Often the analysis will be performed at least at each end of a group ofblocks.

In connection with the current embodiment, groups of 10 contiguousblocks will be identified and used to determine the value with theminimal match of spectral maxima, peaks. More specifically, for eachgroup of 10 blocks, the average of the maximum peak values in each blockand the average of the minimum peak values in each block will becalculated.

These values will then be utilized according to the present embodimentto screen the peaks that will subsequently be used. For example, athreshold value might be selected which sets a minimum as to thespectral matches that will used subsequently: e.g., spectral peaks belowthis value will not be counted. Alternatively, if the number of matchingpeaks within a signal block is significantly higher than a predeterminedcount threshold, the block will be flagged as a noise impaired signalblock. In some embodiments, the sensitivity of the detection will beadjustable with a threshold factor (e.g., a multiplier) Parameter P1,which can be selected by the user 150. As an example, P1 might be basedon some measure of the variability of the minima so that peaks thatexceed P1 will be those peaks that are statistically higher than theaverage (e.g., one standard deviation higher). A P1 might also be usedin connection with an analysis of the number of matching peaks betweenthe noise signal and the subject signal as modified by thresholding orother screening.

In other embodiments, rather than using the spectral values, counts ofthe number of matching peaks will be used instead. That is, thisvariation the number of matching peaks within each block will bedetermined. The average number of matches in all blocks will then becalculated. Then, those blocks that have an above average number ofmatches will be flagged as having noise present therein. In some cases,a numerical threshold might be imposed so that only those counts thatexceed the average by some designated amount (e.g., by some percentageof the average, by a multiple of the standard deviation of the counts inthat group, etc.) would be designated as being contaminated by noise.

In a further preferred step the neighboring (e.g., contiguous) blocks ofthe signal blocks in the target that are designated as impaired will beinspected to determine if the number of matching spectral maxima areslightly (e.g., 10%) above the average value of the average count ofspectral matches in a block. In this case the signal block will also beidentified as an impaired signal block.

With respect to a stereo recording, the same process could then beapplied to the corresponding signal section of the other stereo channel,if such is available. If a signal block of one stereo channel isdetermined to be an impaired signal block, the signal block of the otherstereo channel could also be assigned this property, provided that thedetermined number of matching spectral maxima is slightly above theaverage value for the minimum spectral maxima matching. Of course, as anexample, depending on the original placement of the microphones thatcollected the target signal, it is certainly possible that a noisesource might be present on one channel but not the other or that thenoise characteristics on two channels might be different. In such aninstance, the two channels might be processed separately according tothe methods taught herein.

Turning next to the example of FIG. 2, next the removal of theinterfering signal from the target signal is performed with an adaptivefilter that operates in the frequency domain 215. Note that in the textthat follows, some of the steps that are called for are well known tothose of ordinary skill in the art (e.g., Fourier transform) and, assuch, details related to these steps will not be explained in fullherein.

As an initial step and according to the embodiment of FIG. 2, the inputsignal 200 will be partitioned into overlapping blocks 205, a windowingfunction will be utilized as described previously, and a FFT (or othertransform) will be used to transform the signal into the frequencydomain 210, thereby producing a complex spectrum.

Next, the resulting complex spectrum of the input will be multiplied bya short time invariant filter function that is designed to remove orattenuate the noise relative to the target signal. The next stepaccording to this embodiment will transform the filtered spectrum backinto the time domain via an inverse FFT, followed by a windowingoperation 220 and a summation or other compilation of the individualtime-domain blocks 225 to construct a non-windowed and filtered signal.

The transfer function of the filter will be subjected to temporalsmoothing to reduce artifacts (chirping artifacts, for example) 240before application to the target signal. The time constants used thecontrol the decline and rise of the smoothing filter can be definedseparately in the some embodiments. Continuing with the present example,the input signal will next be mixed with the filtered signal. If incomponent B a section is determined to be undisturbed 245, the mixingratio will be changed according to the setup of parameter P4 (whichmight be allowed to vary between 0.0 and 1.0) in such a way that theportion of the unfiltered input signal in the combination increasesaccordingly 250. In an embodiment it may not be necessary to apply thefiltering process to the sections that have been flagged as undisturbedif the interference signal also contains noise and buzzing sounds whichimpair the input signal continuously.

Turning next to FIGS. 3 and 4, these figures illustrate an embodiment ofa temporal curve of the sort used to detect contiguous impaired sectionsin an audio signal that contain speech content that is partiallyimpaired. In FIG. 3, the curve 310 depicts the number of matchingspectral maxima within each signal block. Line 320 represents theaverage value for the minimum of the contiguous spectral maxima. Thevertical axis is the number of matching spectral peaks between thetarget signal and the noise signal in each window. The horizontal axisis the window number within the target signal.

FIG. 4 illustrates an embodiment of the previous analysis and detectionstep in a subsequent stage wherein some windows have been categorized asbeing impaired. The curve 410 is the same as curve 310 and depicts thenumber of matching spectral maxima for each signal block. The regionsthat are delimited by the line 420 correspond to sections of the targetsignal that have been identified as impaired sections.

Now turning to the embodiment of FIG. 5, in a next preferred step thetransfer function of the adaptive filter will be determined. Thecalculation of the transfer function is implemented via the process ofspectral subtraction (as that term is known and used by those ofordinary skill in the art) using the results of the analysis of thematching spectral maxima (peaks) of the short time magnitude of theimpaired input signal and the short time magnitude of the noise signalwith highest matching to the impaired signal block. The short timemagnitudes and the information about the existing spectral maxima of theinterference signal are provided by the results of the analysis carriedout by Component A. Note that in some embodiments a separatelycalculated adaptive filter might be applied to each block, to eachgroups of blocks (e.g., 10 blocks), or a single calculated adaptivefilter might be applied to the entire input signal.

According to one embodiment, the short time magnitude of the noiseimpaired signal can be determined by implementing the following steps asset out in the example of FIG. 5. First, a digitized audio input signalcontaining noise-only (or predominantly noise) will be accessed 500,e.g., read from disk, read in real time from a microphone, extractedfrom a video clip, etc. That signal will then be partitioned into blocks505, windowed 510 and transformed to the frequency domain 515(preferably via a FFT). The Component A results will be provided (box454) as indicated in FIG. 5 which might include the short time magnitudeof the interfering signal that has the highest match to the impairedsignal block (box 550) as well as the spectral maxima of the peaks withthe highest match to the impaired signal block (box 555).

This will be followed by a determination of the absolute value of theshort time spectral magnitudes 515 within each window. In thisembodiment the steps of windowing and transformation into the frequencydomain will be performed in a manner that is analogous to the stepsdiscussed previously in connection with the processing of the digitaltarget signal.

Continuing with the current example, the process of spectral subtractionwill be used to determine the transfer function by subtracting the shorttime magnitude of the interference signal from the associated short timemagnitude of the impaired input signal (box 535) according to methodswell know to those of ordinary skill in the art. The Parameter P2 hasbeen provided so that a user can adjust the amplitude of the spread ofthe impairment 525 (e.g., the range of spectral amplitudes that areconsidered to be dominant, e.g., amplitudes of frequencies that fall 10%of the maximum amplitude) and Parameter P3 can be utilized to adjust thebandwidth of the filter 530 by, for example, restricting the range offrequencies that are considered for matching purposes. For matchingspectral maxima (peaks) of the short time magnitude of the impairedinput signal and the associated short time magnitude of the interferencesignal the transfer function can be set to the value zero 540, therebyfiltering the target signal so as to attenuate the matching frequencies.

If the value of the parameter P3 is chosen to be relatively low, thecontribution of the spectral subtraction in the calculation of thetransfer function (box 560) of the filter will be deemphasized. In thiscase the transfer function will be primarily defined by the matchingpeaks. Thus, only relevant frequency components of the noise signal willbe removed from the target, which provides an advantage in that thedamage to the target signal will be reduced. In case of interferingsignals with minimal changes in frequency behavior (stationary behavior)this approach presents a sensible alternative to a complete removal ofthe interfering signal.

After each of the blocks has been filtered and transformed back into thetime domain, the filtered blocks will be reassembled to form a modifiedversion of the target signal in which the noise signal has beenattenuated. The final product would then be available to be performedfor a user. In FIG. 6 the performance might take place using the speakerin a user's computer, as one specific example.

The instant invention might be particularly useful in processing theaudio component of a video recording to improve the conversation (orother signal component) therein. It could also be used to attenuatecrowd noise during the recording of a live music concert or live speech,among many other uses. It could also be used to attenuate zoom motornoise in video recordings.

Note that for purposes of the instant disclosure that when a “noisesignal” or an “impairment signal” is referred to herein, that termshould be broadly construed to include instances where there might besome of the signal which it is desired to enhance relative to noise(e.g., speech) within the noise signal but where the noise signalpredominantly contains contaminating noise which is it desired todeemphasize or remove from the target signal. The noise signal might beconventional (e.g., white noise, 60 Hz noise, engine noise, etc.) or itmight be, for example, music that is playing while an individual istalking. In short, the “noise signal” will be any component of therecorded audio other than the information which it is desired to enhance(e.g., speech).

Note further that when the term “average” is used herein, that termshould be broadly construed to include any measure of central tendency(e.g., mean, median, mode, etc.).

Note still further that the method described above could be successivelyapplied to an arbitrarily long target signal (i.e., Components A-D wouldbe applied at a number of different points in the target signal untilthe entire signal was processed). In that way, nonstationarity in thenoise signal could readily be accommodated.

In summary, the instant invention provides a substantial improvement forboth novice and professional users when editing audio recordings andprimarily for attenuating interference signals in speech signals ofvideo recordings. The instant invention requires minimal userinteraction, no definition of multiple parameters, it is an automaticprocess that analyzes the input signal and incorporates specificprocesses to process the input signal and to remove interference signalswithout overly harming the input signal.

Conclusions

While this invention is susceptible of embodiment in many differentforms, there is shown in the drawings, and will herein be describedhereinafter in detail, some specific embodiments of the instantinvention. It should be understood, however, that the present disclosureis to be considered an exemplification of the principles of theinvention and is not intended to limit the invention to the specificembodiments or algorithms so described.

It is to be understood that the terms “including”, “comprising”,“consisting” and grammatical variants thereof do not preclude theaddition of one or more components, features, steps, or integers orgroups thereof and that the terms are to be construed as specifyingcomponents, features, steps or integers.

If the specification or claims refer to “an additional” element, thatdoes not preclude there being more than one of the additional element.

It is to be understood that where the claims or specification refer to“a” or “an” element, such reference is not be construed that there isonly one of that element.

It is to be understood that where the specification states that acomponent, feature, structure, or characteristic “may”, “might”, “can”or “could” be included, that particular component, feature, structure,or characteristic is not required to be included.

Where applicable, although state diagrams, flow diagrams or both may beused to describe embodiments, the invention □ is not limited to thosediagrams or to the corresponding descriptions. For example, flow neednot move through each illustrated box or state, or in exactly the sameorder as illustrated and described.

Methods of the present invention may be implemented by performing orcompleting manually, automatically, or a combination thereof, selectedsteps or tasks.

The term “method” may refer to manners, means, techniques and proceduresfor accomplishing a given task including, but not limited to, thosemanners, means, techniques and procedures either known to, or readilydeveloped from known manners, means, techniques and procedures bypractitioners □ of the art to which the invention belongs.

The term “at least” followed by a number is used herein to denote thestart of a range beginning with that number (which may be a rangerhaving an upper limit or no upper limit, depending on the variable beingdefined). For example, “at least 1” means 1 or more than 1. The term “atmost” followed by a number is used herein to denote the end of a rangeending with that number (which may be a range having 1 or 0 as its lowerlimit, or a range having no lower limit, depending upon the variablebeing defined). For example, “at most 4” means 4 or less than 4, and “atmost 40%” means 40% or less than 40%. Terms of approximation (e.g.,“about”, “substantially”, “approximately”, etc.) should be interpretedaccording to their ordinary and customary meanings as used in theassociated art unless indicated otherwise. Absent a specific definitionand absent ordinary and customary usage in the associated art, suchterms should be interpreted to be ±10% of the base value.

When, in this document, a range is given as “(a first number) to (asecond number)” or “(a first number)-(a second number)”, this means arange whose lower limit is the first number and whose upper limit is thesecond number. For example, 25 to 100 should be interpreted to mean arange whose lower limit is 25 and whose upper limit is 100.Additionally, it should be noted that where a range is given, everypossible subrange or interval within that range is also specificallyintended unless the context indicates to the contrary. For example, ifthe specification indicates a range of 25 to 100 such range is alsointended to include subranges such as 26-100, 27-100, etc., 25-99,25-98, etc., as well as any other possible combination of lower andupper values within the stated range, e.g., 33-47, 60-97, 41-45, 28-96,etc. Note that integer range values have been used in this paragraph forpurposes of illustration only and decimal and fractional values (e.g.,46.7-91.3) should also be understood to be intended as possible subrangeendpoints unless specifically excluded.

It should be noted that where reference is made herein to a methodcomprising two or more defined steps, the defined steps can be carriedout in any order or simultaneously (except where context excludes thatpossibility), and the method can also include one or more other stepswhich are carried out before any of the defined steps, between two ofthe defined steps, or after all of the defined steps (except wherecontext excludes that possibility).

While this invention is susceptible of embodiment in many differentforms, there is shown in the drawings, and is herein described indetail, some specific embodiments. It should be understood, however,that the present disclosure is to be considered an exemplification ofthe principles of the invention and is not intended to limit it to thespecific embodiments or algorithms so described. Those of ordinary skillin the art will be able to make various changes and furthermodifications, apart from those shown or suggested herein, withoutdeparting from the spirit of the inventive concept, the scope of whichis to be determined by the following claims.

Further, it should be noted that terms of approximation (e.g., “about”,“substantially”, “approximately”, etc.) are to be interpreted accordingto their ordinary and customary meanings as used in the associated artunless indicated otherwise herein. Absent a specific definition withinthis disclosure, and absent ordinary and customary usage in theassociated art, such terms should be interpreted to be plus or minus 10%of the base value

Of course, many modifications and extensions could be made to theinstant invention by those of ordinary skill in the art. For example inone preferred embodiment the instant invention will provide an automaticmode, which automatically attenuates video recordings in video cameras,therewith providing video recordings with improved quality audio.

Thus, the present invention is well adapted to carry out the objects andattain the ends and advantages mentioned above as well as those inherenttherein. While the inventive device has been described and illustratedherein by reference to certain preferred embodiments in relation to thedrawings attached thereto, various changes and further modifications,apart from those shown or suggested herein, may be made therein by thoseof ordinary skill in the art, without departing from the spirit of theinventive concept the scope of which is to be determined by thefollowing claims.

What is claimed is:
 1. A method of attenuating a noise signal within aninput signal containing a target signal, and said noise signal,comprising the steps of: a. obtaining a digital representation of theinput signal; b. obtaining a digital representation of the noise signal;c. partitioning said digital representation of the input signal into aplurality of overlapping input windows; d. selecting one or more of saidinput windows; e. calculating a input frequency spectrum from each ofsaid selected input windows; f. determining two or more dominant peakswithin each of said input window spectra, each of said dominant inputfrequency peaks corresponding to a dominant signal frequency; g.partitioning said digital representation of the noise signal into aplurality of overlapping noise windows; h. selecting one or more of saidnoise windows; i. calculating a noise frequency spectrum from each ofsaid selected noise windows; j. using any of said calculated noisefrequency spectra to identify two or more dominant noise frequency peaksand a corresponding two or more dominant noise frequencies; k. for eachof said input windows, matching its dominant signal frequency peaks withsaid dominant noise frequency peaks; l. for each of said input windows,obtaining a count of a number of dominant signal frequency peaks thatmatch said dominant noise frequency peaks; m. calculating an averagecount from all of said counts obtained from each of said input windows;n. identifying each input window whose count is greater than saidaverage count; o. for each identified input window, using at least aportion of said matching frequencies within said identified input windowto construct a transfer function for said identified input window andapplying said transfer function to said identified input window, therebyproducing a filtered block; p. combining each of said filtered blockscorresponding to each of said input windows and any of said inputwindows not identified to form a filtered input signal, therebyattenuating said noise signal within said target signal relative to saidtarget signal; and, q. performing at least a portion of said filteredinput signal for a user.
 2. The method according to claim 1, whereinstep (c) comprises the step of partitioning said digital representationof the input signal into ten overlapping input windows.
 3. The methodaccording to claim 1, wherein step (n) comprises the step of identifyingeach input window whose count is greater than 50 and less than
 250. 4.The method according to claim 1, wherein step (n) comprises the stepsof: (n1) identifying each input window whose count is greater than saidaverage count, (n2) for at least one of said identified each inputwindow, identifying an adjacent input window if an adjacent input windowcount is greater than said average count.
 5. The method according toclaim 1, wherein said transfer function of step (o) is constructed usingspectral subtraction.
 6. The method according to claim 5, wherein saidtransfer function of step (o) is constructed using spectral subtractionand wherein said matching frequencies in said transfer function are setto zeros.